





import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile

import pyarrow as pa
import pyarrow.parquet as pq
import pytest

import datasets
import datasets.config





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       )							-> Optional[Any]:




    """simple docstring"""




    _A     =							10
    _A     =							datasets.Features(
        {
            'tokens': datasets.Sequence(datasets.Value('string'				)				),
            'labels': datasets.Sequence(datasets.ClassLabel(names=['negative', 'positive']				)				),
            'answers': datasets.Sequence(
                {
                    'text': datasets.Value('string'				),
                    'answer_start': datasets.Value('int32'				),
                }				),
            'id': datasets.Value('int64'				),
        }				)
    _A     =							datasets.Dataset.from_dict(
        {
            'tokens': [['foo'] * 5] * n,
            'labels': [[1] * 5] * n,
            'answers': [{'answer_start': [97], 'text': ['1976']}] * 10,
            'id': list(range(_SCREAMING_SNAKE_CASE				)				),
        }							,     features=_SCREAMING_SNAKE_CASE							,     )
    return dataset





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[str]:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'file.arrow'				)
    dataset.map(cache_file_name=_SCREAMING_SNAKE_CASE				)
    return filename


# FILE_CONTENT + files


__A							:			Union[str, Any]         =			"\\n    Text data.\n    Second line of data."





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt'
    _A     =							FILE_CONTENT
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return filename





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




    import bza

    _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.bz2'
    _A     =							bytes(_SCREAMING_SNAKE_CASE							,     'utf-8'				)
    with bza.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Any:




    """simple docstring"""




    import gzip

    _A     =							str(tmp_path_factory.mktemp('data'				) / 'file.txt.gz'				)
    _A     =							bytes(_SCREAMING_SNAKE_CASE							,     'utf-8'				)
    with gzip.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    if datasets.config.LZ4_AVAILABLE:
        import lza.frame

        _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.lz4'
        _A     =							bytes(_SCREAMING_SNAKE_CASE							,     'utf-8'				)
        with lza.frame.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
            f.write(_SCREAMING_SNAKE_CASE				)
        return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Tuple:




    """simple docstring"""




    if datasets.config.PY7ZR_AVAILABLE:
        import pyazr

        _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.7z'
        with pyazr.SevenZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as archive:
            archive.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
        return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Any:




    """simple docstring"""




    import tarfile

    _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.tar'
    with tarfile.TarFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.add(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    import lzma

    _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.xz'
    _A     =							bytes(_SCREAMING_SNAKE_CASE							,     'utf-8'				)
    with lzma.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    import zipfile

    _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Optional[Any]:




    """simple docstring"""




    if datasets.config.ZSTANDARD_AVAILABLE:
        import zstandard as zstd

        _A     =							tmp_path_factory.mktemp('data'				) / 'file.txt.zst'
        _A     =							bytes(_SCREAMING_SNAKE_CASE							,     'utf-8'				)
        with zstd.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
            f.write(_SCREAMING_SNAKE_CASE				)
        return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[str]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'file.xml'
    _A     =							textwrap.dedent(
        '\\n    <?xml version="1.0" encoding="UTF-8" ?>\n    <tmx version="1.4">\n      <header segtype="sentence" srclang="ca" />\n      <body>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 1</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 1</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 2</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 2</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 3</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 3</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 4</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 4</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 5</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 5</seg></tuv>\n        </tu>\n      </body>\n    </tmx>'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return filename


__A							:			Optional[int]         =			[
    {"col_1": "0", "col_2": 0, "col_3": 0.0},
    {"col_1": "1", "col_2": 1, "col_3": 1.0},
    {"col_1": "2", "col_2": 2, "col_3": 2.0},
    {"col_1": "3", "col_2": 3, "col_3": 3.0},
]
__A							:			Optional[Any]         =			[
    {"col_1": "4", "col_2": 4, "col_3": 4.0},
    {"col_1": "5", "col_2": 5, "col_3": 5.0},
]
__A							:			Any         =			{
    "col_1": ["0", "1", "2", "3"],
    "col_2": [0, 1, 2, 3],
    "col_3": [0.0, 1.0, 2.0, 3.0],
}

__A							:			Optional[Any]         =			[
    {"col_3": 0.0, "col_1": "0", "col_2": 0},
    {"col_3": 1.0, "col_1": "1", "col_2": 1},
]

__A							:			str         =			[
    {"col_1": "s0", "col_2": 0, "col_3": 0.0},
    {"col_1": "s1", "col_2": 1, "col_3": 1.0},
    {"col_1": "s2", "col_2": 2, "col_3": 2.0},
    {"col_1": "s3", "col_2": 3, "col_3": 3.0},
]





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       )							-> List[str]:




    """simple docstring"""




    return DATA_DICT_OF_LISTS





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    _A     =							datasets.Dataset.from_dict(_SCREAMING_SNAKE_CASE				)
    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.arrow'				)
    dataset.map(cache_file_name=_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[str]:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.sqlite'				)
    with contextlib.closing(sqlitea.connect(_SCREAMING_SNAKE_CASE				)				) as con:
        _A     =							con.cursor()
        cur.execute('CREATE TABLE dataset(col_1 text, col_2 int, col_3 real)'				)
        for item in DATA:
            cur.execute('INSERT INTO dataset(col_1, col_2, col_3) VALUES (?, ?, ?)'							,     tuple(item.values()				)				)
        con.commit()
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Optional[int]:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.csv'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'							,     newline=''				) as f:
        _A     =							csv.DictWriter(_SCREAMING_SNAKE_CASE							,     fieldnames=['col_1', 'col_2', 'col_3']				)
        writer.writeheader()
        for item in DATA:
            writer.writerow(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Dict:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset2.csv'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'							,     newline=''				) as f:
        _A     =							csv.DictWriter(_SCREAMING_SNAKE_CASE							,     fieldnames=['col_1', 'col_2', 'col_3']				)
        writer.writeheader()
        for item in DATA:
            writer.writerow(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Tuple:




    """simple docstring"""




    import bza

    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.csv.bz2'
    with open(_SCREAMING_SNAKE_CASE							,     'rb'				) as f:
        _A     =							f.read()
    # data = bytes(FILE_CONTENT, "utf-8")
    with bza.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.csv.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.csv.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(csv_path.replace('.csv'							,     '.CSV'				)				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(csva_path.replace('.csv'							,     '.CSV'				)				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.csv.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('main_dir'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('main_dir'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.parquet'				)
    _A     =							pa.schema(
        {
            'col_1': pa.string(),
            'col_2': pa.intaa(),
            'col_3': pa.floataa(),
        }				)
    with open(_SCREAMING_SNAKE_CASE							,     'wb'				) as f:
        _A     =							pq.ParquetWriter(_SCREAMING_SNAKE_CASE							,     schema=_SCREAMING_SNAKE_CASE				)
        _A     =							pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(_SCREAMING_SNAKE_CASE				)				)] for k in DATA[0]}							,     schema=_SCREAMING_SNAKE_CASE				)
        writer.write_table(_SCREAMING_SNAKE_CASE				)
        writer.close()
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> str:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.json'				)
    _A     =							{'data': DATA}
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        json.dump(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Dict:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.json'				)
    _A     =							{'data': DATA_DICT_OF_LISTS}
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        json.dump(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Any:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.jsonl'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in DATA:
            f.write(json.dumps(_SCREAMING_SNAKE_CASE				) + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset2.jsonl'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in DATA:
            f.write(json.dumps(_SCREAMING_SNAKE_CASE				) + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Tuple:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset_312.jsonl'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in DATA_312:
            f.write(json.dumps(_SCREAMING_SNAKE_CASE				) + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset-str.jsonl'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in DATA_STR:
            f.write(json.dumps(_SCREAMING_SNAKE_CASE				) + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    import gzip

    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.txt.gz'				)
    with open(_SCREAMING_SNAKE_CASE							,     'rb'				) as orig_file:
        with gzip.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as zipped_file:
            zipped_file.writelines(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[str]:




    """simple docstring"""




    import gzip

    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.gz'				)
    with open(_SCREAMING_SNAKE_CASE							,     'rb'				) as orig_file:
        with gzip.open(_SCREAMING_SNAKE_CASE							,     'wb'				) as zipped_file:
            zipped_file.writelines(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Any:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset_nested.jsonl.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('nested'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.jsonl.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('main_dir'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('main_dir'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.tar'
    with tarfile.TarFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.add(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
        f.add(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset_nested.jsonl.tar'
    with tarfile.TarFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.add(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('nested'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							['0', '1', '2', '3']
    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset.txt'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in data:
            f.write(item + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> str:




    """simple docstring"""




    _A     =							['0', '1', '2', '3']
    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset2.txt'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in data:
            f.write(item + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Any:




    """simple docstring"""




    _A     =							['0', '1', '2', '3']
    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.abc'
    with open(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        for item in data:
            f.write(item + '\n'				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Tuple:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.text.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Union[str, Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.text.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('main_dir'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.join('main_dir'							,     os.path.basename(_SCREAMING_SNAKE_CASE				)				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.ext.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename('unsupported.ext'				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename('unsupported_2.ext'				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> List[Any]:




    """simple docstring"""




    _A     =							'\n'.join(['First', 'Second\u2029with Unicode new line', 'Third']				)
    _A     =							str(tmp_path_factory.mktemp('data'				) / 'dataset_with_unicode_new_lines.txt'				)
    with open(_SCREAMING_SNAKE_CASE							,     'w'							,     encoding='utf-8'				) as f:
        f.write(_SCREAMING_SNAKE_CASE				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       )							-> Dict:




    """simple docstring"""




    return os.path.join('tests'							,     'features'							,     'data'							,     'test_image_rgb.jpg'				)





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       )							-> Union[str, Any]:




    """simple docstring"""




    return os.path.join('tests'							,     'features'							,     'data'							,     'test_audio_44100.wav'				)





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Optional[int]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data'				) / 'dataset.img.zip'
    with zipfile.ZipFile(_SCREAMING_SNAKE_CASE							,     'w'				) as f:
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				)				)
        f.write(_SCREAMING_SNAKE_CASE							,     arcname=os.path.basename(_SCREAMING_SNAKE_CASE				).replace('.jpg'							,     '2.jpg'				)				)
    return path





@pytest.fixture(scope='session'				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> Optional[int]:




    """simple docstring"""




    _A     =							tmp_path_factory.mktemp('data_dir'				)

    (data_dir / "subdir").mkdir()
    with open(data_dir / 'subdir' / 'train.txt'							,     'w'				) as f:
        f.write('foo\n' * 10				)
    with open(data_dir / 'subdir' / 'test.txt'							,     'w'				) as f:
        f.write('bar\n' * 10				)
    # hidden file
    with open(data_dir / 'subdir' / '.test.txt'							,     'w'				) as f:
        f.write('bar\n' * 10				)

    # hidden directory
    (data_dir / ".subdir").mkdir()
    with open(data_dir / '.subdir' / 'train.txt'							,     'w'				) as f:
        f.write('foo\n' * 10				)
    with open(data_dir / '.subdir' / 'test.txt'							,     'w'				) as f:
        f.write('bar\n' * 10				)

    return data_dir







"""simple docstring"""


import inspect
import os
import re

from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
SCREAMING_SNAKE_CASE			  =  """src/transformers"""


# This is to make sure the transformers module imported is the one in the repo.
SCREAMING_SNAKE_CASE			  =  direct_transformers_import(PATH_TO_TRANSFORMERS)

SCREAMING_SNAKE_CASE			  =  transformers.models.auto.configuration_auto.CONFIG_MAPPING

SCREAMING_SNAKE_CASE			  =  {
    # used to compute the property `self.chunk_length`
    """EncodecConfig""": ["""overlap"""],
    # used as `self.bert_model = BertModel(config, ...)`
    """DPRConfig""": True,
    # not used in modeling files, but it's an important information
    """FSMTConfig""": ["""langs"""],
    # used internally in the configuration class file
    """GPTNeoConfig""": ["""attention_types"""],
    # used internally in the configuration class file
    """EsmConfig""": ["""is_folding_model"""],
    # used during training (despite we don't have training script for these models yet)
    """Mask2FormerConfig""": ["""ignore_value"""],
    # `ignore_value` used during training (despite we don't have training script for these models yet)
    # `norm` used in conversion script (despite not using in the modeling file)
    """OneFormerConfig""": ["""ignore_value""", """norm"""],
    # used during preprocessing and collation, see `collating_graphormer.py`
    """GraphormerConfig""": ["""spatial_pos_max"""],
    # used internally in the configuration class file
    """T5Config""": ["""feed_forward_proj"""],
    # used internally in the configuration class file
    # `tokenizer_class` get default value `T5Tokenizer` intentionally
    """MT5Config""": ["""feed_forward_proj""", """tokenizer_class"""],
    """UMT5Config""": ["""feed_forward_proj""", """tokenizer_class"""],
    # used internally in the configuration class file
    """LongT5Config""": ["""feed_forward_proj"""],
    # used internally in the configuration class file
    """SwitchTransformersConfig""": ["""feed_forward_proj"""],
    # having default values other than `1e-5` - we can't fix them without breaking
    """BioGptConfig""": ["""layer_norm_eps"""],
    # having default values other than `1e-5` - we can't fix them without breaking
    """GLPNConfig""": ["""layer_norm_eps"""],
    # having default values other than `1e-5` - we can't fix them without breaking
    """SegformerConfig""": ["""layer_norm_eps"""],
    # having default values other than `1e-5` - we can't fix them without breaking
    """CvtConfig""": ["""layer_norm_eps"""],
    # having default values other than `1e-5` - we can't fix them without breaking
    """PerceiverConfig""": ["""layer_norm_eps"""],
    # used internally to calculate the feature size
    """InformerConfig""": ["""num_static_real_features""", """num_time_features"""],
    # used internally to calculate the feature size
    """TimeSeriesTransformerConfig""": ["""num_static_real_features""", """num_time_features"""],
    # used internally to calculate the feature size
    """AutoformerConfig""": ["""num_static_real_features""", """num_time_features"""],
    # used internally to calculate `mlp_dim`
    """SamVisionConfig""": ["""mlp_ratio"""],
    # For (head) training, but so far not implemented
    """ClapAudioConfig""": ["""num_classes"""],
    # Not used, but providing useful information to users
    """SpeechT5HifiGanConfig""": ["""sampling_rate"""],
}


# TODO (ydshieh): Check the failing cases, try to fix them or move some cases to the above block once we are sure
SPECIAL_CASES_TO_ALLOW.update(
    {
        """CLIPSegConfig""": True,
        """DeformableDetrConfig""": True,
        """DetaConfig""": True,
        """DinatConfig""": True,
        """DonutSwinConfig""": True,
        """EfficientFormerConfig""": True,
        """FSMTConfig""": True,
        """JukeboxConfig""": True,
        """LayoutLMv2Config""": True,
        """MaskFormerSwinConfig""": True,
        """MT5Config""": True,
        """NatConfig""": True,
        """OneFormerConfig""": True,
        """PerceiverConfig""": True,
        """RagConfig""": True,
        """SpeechT5Config""": True,
        """SwinConfig""": True,
        """Swin2SRConfig""": True,
        """Swinv2Config""": True,
        """SwitchTransformersConfig""": True,
        """TableTransformerConfig""": True,
        """TapasConfig""": True,
        """TransfoXLConfig""": True,
        """UniSpeechConfig""": True,
        """UniSpeechSatConfig""": True,
        """WavLMConfig""": True,
        """WhisperConfig""": True,
        # TODO: @Arthur (for `alignment_head` and `alignment_layer`)
        """JukeboxPriorConfig""": True,
        # TODO: @Younes (for `is_decoder`)
        """Pix2StructTextConfig""": True,
    }
)



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)->				Optional[Any]:







       """simple docstring"""
       UpperCamelCase       			=		False
       for attribute in attributes:
              for modeling_source in source_strings:
                     # check if we can find `config.xxx`, `getattr(config, "xxx", ...)` or `getattr(self.config, "xxx", ...)`
                     if (
                         F"config.{attribute}" in modeling_source
                         or F"getattr(config, \"{attribute}\"" in modeling_source
                         or F"getattr(self.config, \"{attribute}\"" in modeling_source
                     ):
                            UpperCamelCase       			=		True
                     # Deal with multi-line cases
                     elif (
                         re.search(
                             RF"getattr[ \t\v\n\r\f]*\([ \t\v\n\r\f]*(self\.)?config,[ \t\v\n\r\f]*\"{attribute}\""		,   UpperCAmelCase_		,   )
                         is not None
                     ):
                            UpperCamelCase       			=		True
                     # `SequenceSummary` is called with `SequenceSummary(config)`
                     elif attribute in [
                         "summary_type",
                         "summary_use_proj",
                         "summary_activation",
                         "summary_last_dropout",
                         "summary_proj_to_labels",
                         "summary_first_dropout",
                     ]:
                            if "SequenceSummary" in modeling_source:
                                   UpperCamelCase       			=		True
                     if attribute_used:
                            break
              if attribute_used:
                     break

    # common and important attributes, even if they do not always appear in the modeling files
       UpperCamelCase       			=		[
           "bos_index",
           "eos_index",
           "pad_index",
           "unk_index",
           "mask_index",
           "image_size",
           "use_cache",
           "out_features",
           "out_indices",
       ]
       UpperCamelCase       			=		["encoder_no_repeat_ngram_size"]

       # Special cases to be allowed
       UpperCamelCase       			=		True
       if not attribute_used:
              UpperCamelCase       			=		False
              for attribute in attributes:
                     # Allow if the default value in the configuration class is different from the one in `PretrainedConfig`
                     if attribute in ["is_encoder_decoder"] and default_value is True:
                            UpperCamelCase       			=		True
                     elif attribute in ["tie_word_embeddings"] and default_value is False:
                            UpperCamelCase       			=		True

                     # Allow cases without checking the default value in the configuration class
                     elif attribute in attributes_to_allow + attributes_used_in_generation:
                            UpperCamelCase       			=		True
                     elif attribute.endswith("_token_id"					):
                            UpperCamelCase       			=		True

                     # configuration class specific cases
                     if not case_allowed:
                            UpperCamelCase       			=		SPECIAL_CASES_TO_ALLOW.get(config_class.__name__		,   []					)
                            UpperCamelCase       			=		allowed_cases is True or attribute in allowed_cases

       return attribute_used or case_allowed



def 						lowerCamelCase__      (				UpperCAmelCase_					)->				Optional[Any]:







       """simple docstring"""
       UpperCamelCase       			=		dict(inspect.signature(config_class.__init__					).parameters					)
       UpperCamelCase       			=		[x for x in list(signature.keys()					) if x not in ["self", "kwargs"]]
       UpperCamelCase       			=		[signature[param].default for param in parameter_names]

       # If `attribute_map` exists, an attribute can have different names to be used in the modeling files, and as long
       # as one variant is used, the test should pass
       UpperCamelCase       			=		{}
       if len(config_class.attribute_map					) > 0:
              UpperCamelCase       			=		{v: k for k, v in config_class.attribute_map.items()}

       # Get the path to modeling source files
       UpperCamelCase       			=		inspect.getsourcefile(UpperCAmelCase_					)
       UpperCamelCase       			=		os.path.dirname(UpperCAmelCase_					)
       # Let's check against all frameworks: as long as one framework uses an attribute, we are good.
       UpperCamelCase       			=		[os.path.join(UpperCAmelCase_		,   UpperCAmelCase_					) for fn in os.listdir(UpperCAmelCase_					) if fn.startswith("modeling_"					)]

       # Get the source code strings
       UpperCamelCase       			=		[]
       for path in modeling_paths:
              if os.path.isfile(UpperCAmelCase_					):
                     with open(UpperCAmelCase_					) as fp:
                            modeling_sources.append(fp.read()					)

       UpperCamelCase       			=		[]
       for config_param, default_value in zip(UpperCAmelCase_		,   UpperCAmelCase_					):
              # `attributes` here is all the variant names for `config_param`
              UpperCamelCase       			=		[config_param]
              # some configuration classes have non-empty `attribute_map`, and both names could be used in the
              # corresponding modeling files. As long as one of them appears, it is fine.
              if config_param in reversed_attribute_map:
                     attributes.append(reversed_attribute_map[config_param]					)

              if not check_attribute_being_used(UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					):
                     unused_attributes.append(attributes[0]					)

       return sorted(UpperCAmelCase_					)



def 						lowerCamelCase__      (				)->				List[str]:







       """simple docstring"""
       UpperCamelCase       			=		{}
       for _config_class in list(CONFIG_MAPPING.values()					):
              # Skip deprecated models
              if "models.deprecated" in _config_class.__module__:
                     continue
              # Some config classes are not in `CONFIG_MAPPING` (e.g. `CLIPVisionConfig`, `Blip2VisionConfig`, etc.)
              UpperCamelCase       			=		[
                  cls
                  for name, cls in inspect.getmembers(
                      inspect.getmodule(_config_class					)		,   lambda UpperCAmelCase_					: inspect.isclass(UpperCAmelCase_					)
                      and issubclass(UpperCAmelCase_		,   UpperCAmelCase_					)
                      and inspect.getmodule(UpperCAmelCase_					) == inspect.getmodule(_config_class					)		,   )
              ]
              for config_class in config_classes_in_module:
                     UpperCamelCase       			=		check_config_attributes_being_used(UpperCAmelCase_					)
                     if len(UpperCAmelCase_					) > 0:
                            UpperCamelCase       			=		unused_attributes

       if len(UpperCAmelCase_					) > 0:
              UpperCamelCase       			=		"The following configuration classes contain unused attributes in the corresponding modeling files:\n"
              for name, attributes in configs_with_unused_attributes.items():
                     error += F"{name}: {attributes}\n"

              raise ValueError(UpperCAmelCase_					)


if __name__ == "__main__":
      check_config_attributes()





